Entropy model for determining the necessary information in the diagnostics of maritime transportation

Abstract

The main problem of diagnostics and management of traffic flows under conditions of uncertainty of the impact of the external environment is to obtain the required amount of high-quality information, since in the case of its small values the accuracy of forecasts decreases, and in the case of its redundancy the possibility of its use is hampered. The information-entropy model, which is the substantiation of diagnostics and the required amount of input information in the context of environmental fluctuations is presented in this paper. On the example of studying maritime transportation under conditions of variable conjuncture, the consequences of pandemic and military interventions and other manifestations of environmental impact, the entropy of different values of a priori and a posteriori information is estimated. The main factors of the merchant marine fleet development are the volume of international shipping, the annual growth rate of the merchant fleet, the average age of the fleet, and tariff rates in container transportation. The main trends in the modern development of the world’s maritime fleet are identified. The algorithm for determining the required amount of information with regard to uncertainty is constructed. The experimental verification is carried out taking into account the dynamics of the main indicators of the world merchant fleet. It is shown that entropy is a quantitative measure of input information for managing and diagnosing transport processes under conditions of uncertainty.